Age Estimation and Face Verification Across Aging Using Landmarks
Age estimation and face verification across aging are important problems with a wide range of applications. It is well known that age and identity information are encoded in both texture and shape of the face. Building on recent advances in landmark extraction and statistical techniques for landmark...
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| Published in | IEEE transactions on information forensics and security Vol. 7; no. 6; pp. 1780 - 1788 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
IEEE
01.12.2012
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1556-6013 1556-6021 |
| DOI | 10.1109/TIFS.2012.2213812 |
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| Abstract | Age estimation and face verification across aging are important problems with a wide range of applications. It is well known that age and identity information are encoded in both texture and shape of the face. Building on recent advances in landmark extraction and statistical techniques for landmark-based shape analysis, we consider these problems using facial shapes. We show that by using well-defined shape spaces and their associated geometry, one can obtain significant performance improvements in both age estimation and face verification. Toward this end, we propose to model the facial shapes as points on a Grassmann manifold. Age estimation and face verification are then considered as regression and classification problems on this manifold. Algorithms for regression and classification are designed to take into account the geometry of the underlying space. The proposed method is flexible and can be used as a standalone age estimator or classifier, and we also present methods for fusion with texture-based algorithms. |
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| AbstractList | Age estimation and face verification across aging are important problems with a wide range of applications. It is well known that age and identity information are encoded in both texture and shape of the face. Building on recent advances in landmark extraction and statistical techniques for landmark-based shape analysis, we consider these problems using facial shapes. We show that by using well-defined shape spaces and their associated geometry, one can obtain significant performance improvements in both age estimation and face verification. Toward this end, we propose to model the facial shapes as points on a Grassmann manifold. Age estimation and face verification are then considered as regression and classification problems on this manifold. Algorithms for regression and classification are designed to take into account the geometry of the underlying space. The proposed method is flexible and can be used as a standalone age estimator or classifier, and we also present methods for fusion with texture-based algorithms. |
| Author | Tao Wu Turaga, P. Chellappa, R. |
| Author_xml | – sequence: 1 surname: Tao Wu fullname: Tao Wu email: taowu@umiacs.umd.edu organization: Dept. of Electr. & Comput. Eng., Univ. of Maryland, College Park, MD, USA – sequence: 2 givenname: P. surname: Turaga fullname: Turaga, P. email: pturaga@asu.edu organization: Dept. of Arts Media & Eng., Arizona State Univ., Tempe, AZ, USA – sequence: 3 givenname: R. surname: Chellappa fullname: Chellappa, R. email: rama@umiacs.umd.edu organization: Dept. of Electr. & Comput. Eng., Univ. of Maryland, College Park, MD, USA |
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| SubjectTerms | Age estimation biometrics Estimation Face recognition face verification facial shapes Feature extraction Grassmann manifold Manifolds Shape analysis |
| Title | Age Estimation and Face Verification Across Aging Using Landmarks |
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